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Show Results For
-
All HBS Web
(642)
- News (171)
- Research (326)
- Events (6)
- Multimedia (9)
- Faculty Publications (228)
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its...
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Keywords:
Investor Relations;
Forecasting;
Machine Learning;
Artificial Intelligence;
Apparel;
Corporate Finance;
Forecasting and Prediction;
AI and Machine Learning;
Digital Transformation;
Apparel and Accessories Industry;
United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to...
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- Web
eMarketer/Insider Intelligence | Baker Library | Bloomberg Center | Harvard Business School
Databases eMarketer/Insider Intelligence eMarketer/Insider Intelligence Bookmark This eMarketer/Insider Intelligence /find/databases/emarketer-insider-intelligence Market data,...
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- October 2019 (Revised March 2021)
- Background Note
Modern Automation (B): Robotics
By: William R. Kerr and James Palano
Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new tasks that could be completed by machines had significant...
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Keywords:
Robotics;
Artificial Intelligence;
Future Of Work;
Technology Commercialization;
Information Technology;
Commercialization;
Employment;
AI and Machine Learning
Kerr, William R., and James Palano. "Modern Automation (B): Robotics." Harvard Business School Background Note 820-069, October 2019. (Revised March 2021.)
- August 2018 (Revised October 2019)
- Case
C3.ai—Driven to Succeed
By: Robert Simons and George Gonzalez
CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee...
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Keywords:
Strategy Execution;
Performance Measurement;
Critical Performance Variables;
Strategic Boundaries;
Internet Of Things;
Artificial Intelligence;
Software Development;
Big Data;
Machine Learning;
Business Startups;
Management Style;
Business Strategy;
Performance;
Measurement and Metrics;
Organizational Culture;
AI and Machine Learning;
Digital Transformation;
Applications and Software;
Digital Marketing;
Analytics and Data Science;
Technology Industry;
United States;
California
Simons, Robert, and George Gonzalez. "C3.ai—Driven to Succeed." Harvard Business School Case 119-004, August 2018. (Revised October 2019.)
- Web
Economist Intelligence Unit | Baker Library | Bloomberg Center | Harvard Business School
Databases Economist Intelligence Unit Economist Intelligence Unit Bookmark This Economist Intelligence Unit /find/databases/economist-intelligence-unit In-depth country View Details
- February 2024
- Technical Note
AI Product Development Lifecycle
By: Michael Parzen, Jessie Li and Marily Nika
In this article, we will discuss the concept of AI Products, how they are changing our daily lives, how the field of AI & Product Management is evolving, and the AI Product Development Lifecycle.
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Keywords:
Artificial Intelligence;
Product Management;
Product Life Cycle;
Technology;
AI and Machine Learning;
Product Development
Parzen, Michael, Jessie Li, and Marily Nika. "AI Product Development Lifecycle." Harvard Business School Technical Note 624-070, February 2024.
- Research Summary
Overview
I develop machine learning tools and techniques which enable human decision makers to make better decisions. More specifically, my research addresses the following fundamental questions pertaining to human and algorithmic decision-making:
1. How to build... View Details
1. How to build... View Details
- July 2019
- Teaching Note
Miroglio Fashion
By: Sunil Gupta
Teaching Note for HBS Nos. 519-053, 519-070, and 519-072.
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- 2021
- Article
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
By: Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott and Daniel L.K. Yamins
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include: real-time...
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Keywords:
Artificial Intelligence;
Platform;
Interactive Physical Simulation;
Virtual Environment;
Multi-modal;
AI and Machine Learning
Gan, Chuang, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott, and Daniel L.K. Yamins. "ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 35th (2021).
- March–April 2021
- Article
Network-biased Technical Change: How Information Management Tools Overcome Some Biases but Exacerbate Others.
By: Gerald C. Kane and Lynn Wu
Organizations have long sought to improve employee performance by managing knowledge more effectively. In this paper, we test whether the adoption of digital tools for expertise search and access within an organization, often referred to as a support to an...
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Keywords:
Digital Tools;
Social Media;
Social Networks;
Transactive Memory Systems;
Augmented Intelligence;
Artificial Intelligence;
Social and Collaborative Networks;
Gender;
Equality and Inequality;
Technology Adoption;
Knowledge Management;
Performance Improvement;
Power and Influence;
Organizational Change and Adaptation
Kane, Gerald C., and Lynn Wu. "Network-biased Technical Change: How Information Management Tools Overcome Some Biases but Exacerbate Others." Organization Science 32, no. 2 (March–April 2021): 273–292.
- 2020
- Article
A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?
By: Doug J. Chung, Byungyeon Kim and Niladri B. Syam
Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role...
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Keywords:
Sales Compensation;
Sales Management;
Sales Strategy;
Principal-agent Theory;
Structural Econometrics;
Field Experiments;
Machine Learning;
Artificial Intelligence;
Salesforce Management;
Compensation and Benefits;
Motivation and Incentives;
AI and Machine Learning
Chung, Doug J., Byungyeon Kim, and Niladri B. Syam. "A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?" Foundations and Trends® in Marketing 14, no. 1 (2020): 1–52.
- May 2022 (Revised July 2022)
- Case
The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022
By: David B. Yoffie and Daniel Fisher
In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest...
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Keywords:
Strategy;
Artificial Intelligence;
Deep Learning;
Voice Assistants;
Smart Home;
Market Share;
Globalized Markets and Industries;
Competitive Strategy;
Digital Platforms;
AI and Machine Learning;
Technology Industry;
United States
Yoffie, David B., and Daniel Fisher. "The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022." Harvard Business School Case 722-462, May 2022. (Revised July 2022.)
- 10 Jul 2023
- News
Why Everyone Is Mad about New York’s AI Hiring Law
- October 2015 (Revised October 2016)
- Case
Building Watson: Not So Elementary, My Dear! (Abridged)
By: Willy C. Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the...
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Keywords:
Analytics;
Big Data;
Business Analytics;
Product Development Strategy;
Machine Learning;
Machine Intelligence;
Artificial Intelligence;
Product Development;
AI and Machine Learning;
Information Technology;
Analytics and Data Science;
Information Technology Industry;
United States
Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)
- February 2018
- Case
Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home
By: Rajiv Lal and Scott Johnson
Amazon, Google, and Apple all offer their own smart speaker. The devices represent each firm's entry point into the connected home market. All three companies come into the space with their own strengths and weaknesses. Who will win?
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Keywords:
Apple;
Apple Inc.;
Google;
Amazon;
Amazon.com;
Google Home;
Homepod;
Echo;
Smart Home;
Connected Home;
Voice;
Artificial Intelligence;
Machine Learning;
Internet Of Things;
Smart Speaker;
Connected Speaker;
Intelligent Assistants;
Virtual Assistants;
Voice Assistants;
Alexa;
Google Assistant;
Siri;
Technological Innovation;
Disruptive Innovation;
Competitive Strategy;
Business Strategy;
Adoption;
Information Infrastructure;
Information Technology;
Internet and the Web;
Mobile and Wireless Technology;
Applications and Software;
Technology Adoption;
Digital Platforms;
Household;
AI and Machine Learning;
Electronics Industry;
Technology Industry;
United States
Lal, Rajiv, and Scott Johnson. "Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home." Harvard Business School Case 518-035, February 2018.
- January 2017 (Revised March 2017)
- Case
IBM Transforming, 2012–2016: Ginni Rometty Steers Watson
By: Rosabeth Moss Kanter and Jonathan Cohen
To transform IBM for the next technology wave, Ginni Rometty, who became CEO in 2012, led divestment of declining businesses, made acquisitions in digital innovation and cloud computing, formed partnerships with former competitors such as Apple and tech startups, and...
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Keywords:
Digital;
Technological Change;
Artificial Intelligence;
Data;
IBM;
Watson;
Internet Of Things;
Innovation and Invention;
Management;
Sales;
Information Technology;
Technological Innovation;
Transformation;
AI and Machine Learning
Kanter, Rosabeth Moss, and Jonathan Cohen. "IBM Transforming, 2012–2016: Ginni Rometty Steers Watson." Harvard Business School Case 317-046, January 2017. (Revised March 2017.)
- Article
Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs
By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the...
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Keywords:
Artificial Intelligence;
Diagnosis;
Computer-assisted;
Image Interpretation;
Machine Learning;
Radiography;
Panoramic Radiograph;
AI and Machine Learning
Endres, Michael G., Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland, and Robert A. Gaudin. "Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs." Diagnostics 10, no. 6 (June 2020).
- December 2018
- Case
Choosy
By: Jeffrey J. Bussgang and Julia Kelley
Founded in 2017, Choosy is a data-driven fashion startup that uses algorithms to identify styles trending on social media. After manufacturing similar items using a China-based supply chain, Choosy sells them to consumers through its website and social media pages....
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Keywords:
Artificial Intelligence;
Algorithms;
Machine Learning;
Neural Networks;
Instagram;
Influencer;
Fast Fashion;
Design;
Customer Satisfaction;
Customer Focus and Relationships;
Decision Making;
Cost vs Benefits;
Innovation and Invention;
Brands and Branding;
Product Positioning;
Demand and Consumers;
Supply Chain;
Production;
Logistics;
Business Model;
Expansion;
Internet and the Web;
Mobile and Wireless Technology;
Digital Platforms;
Social Media;
Technology Industry;
Fashion Industry;
North and Central America;
United States;
New York (state, US);
New York (city, NY)
- 2019
- Working Paper
Using Technology to Augment Professionals, Instead of Replacing Them, for Innovative Problem Solving
By: Hila Lifshitz - Assaf, Felicia Ng, Aniket Kittur and Robert Kraut
While in some technological and scientific areas innovation is flourishing, in others it is stalling, leaving important problems unsolved for decades. One explanation is professionals’ limitations as problem solvers, as accumulating depth of knowledge enhances one’s...
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